Image artifact removal technique for LCP

ABSTRACT

A technique is provided that identifies screen and non-screen regions of a projected or displayed image to smooth and selectively remove moiré from the screen regions while maintaining sharpness in the non-screen regions. Each pixel in the image is classified as a screen or non-screen pixel and then pixels in a predetermined surrounding area of each pixel are examined to check the classification of that pixel. A low pass filter is applied to pixels in the image, such that, when the low pass filter is applied, a center of the low pass filter is selectively shifted relative to a current pixel based on the examination.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is related to application entitled “Memory EfficientImage Artifact Removal Technique for LCP,” filed herewith in names ofinventors Jau-Yuen Chen and Joseph Shu and assigned to the assignee ofthis application. The contents of the above-identified relatedapplication are incorporated by reference herein.

BACKGROUND OF THE INVENTION

1. Field of the Invention

This invention relates to a method and apparatus for removing imageartifacts including moiré from screen images, particularly imagesgenerated by liquid crystal projectors (LCPs). The invention alsorelates to a program of instructions for implementing various aspects ofthe image artifact removal technique.

2. Description of the Related Art

An image that contains screens, which are composed of periodic lines ordot patterns, sometimes exhibits artifacts including moiré artifactswhen projected or displayed. Moiré artifacts may result whenever twogeometrically-regular patterns are superimposed and often manifestsitself as a ripple-like pattern in the image representations. Suchartifacts degrade image quality and are therefore undesirable.

In the case of a projected image, the image-generating projection device(e.g., an LCP) may employ a technique known as a “keystone correction”which alters the shape of the projected image to compensate for theangle of projection. While the keystone correction improves certaincharacteristics of the projected image, it has a disadvantage in that itis usually not able to maintain equal spacing between screen line/dotpatterns. Consequently, the unequal spacing at different locations inthe image results in moire artifacts.

While low pass filtering may be used to remove the moiré artifacts,global application of a low pass filter (LPF) tends to cause blurring intext and non-screen regions in the displayed or projected image. Thatis, if an LPF is applied uniformly to the image, the degree of filteringrequired to achieve an acceptable reduction in moiré usually results inan unacceptable reduction in resolution.

Thus, there is a need for an effective image artifact removal techniquethat smoothes screen regions to remove moire while maintaining sharpnessin non-screen regions and that is particularly well suited for projectedimages.

OBJECTS AND SUMMARY OF THE INVENTION

Objects of the Invention

Therefore, it is an object of the present invention to overcome theaforementioned problems by providing such an image artifact removaltechnique.

It is another object of this invention to provide an image artifactremoval technique that identifies and segments screen and non-screenimage regions and treats the two regions separately to remove moire fromthe screen regions while maintaining sharpness in the non-screenregions.

Summary of the Invention

According to one aspect of this invention, a method for removing imageartifacts from an image representation is provided. Such methodcomprises the steps of (a) obtaining a pixel representation of theimage; (b) classifying each pixel in the image as a screen or non-screenpixel; (c) examining pixels in a predetermined surrounding area of eachpixel to check the classification of that pixel as determined in step(b); and (d) selectively applying a low pass filter to pixels in theimage, such that, when the low pass filter is applied, a center of thelow pass filter is selectively shifted relative to a current pixel basedon the examining in step (c).

Various preferred features of the method are set forth below.

The classifying step (b) comprises applying a first mask of apredetermined size centered on the pixel being classified to determineif the center pixel is in an area having a predetermined periodicpattern.

The first mask is divided into a plurality of overlapping areas, thecenter pixel being in each of the first mask areas.

The examining step (c) comprises applying a second mask of apredetermined size centered on the pixel being checked.

The second mask is divided into a plurality of overlapping areas, thecenter pixel being in each of the second mask areas.

The predetermined periodic pattern is a periodic line or dot patternhaving a period of 2 or 3.

The selectively applying step (e) comprises selectively applying the lowpass filter based on which of the plurality of second mask areascontains screen pixels.

The above-described method may further comprise the steps of (f)determining a feature indicator for at least one portion of the image;and (g) adaptively sharpening or softening the at least one portion ofthe image based on the determined feature indicator.

Another aspect of the invention involves an apparatus for removing imageartifacts from a representation of an image. Such apparatus comprises adevice for obtaining a pixel representation of the image; a screen pixelidentifier, in communication with the device, for classifying each pixelin the image as a screen or non-screen pixel; a screen region verifier,in communication with the screen pixel identifier, for examining pixelsin a predetermined surrounding area of each pixel to check theclassification of that pixel as determined by the screen pixelidentifier; and a low pass filter, in communication with the screenregion verifier, that is selectively applied to pixels in the image,such that, when the low pass filter is applied, a center of the low passfilter is selectively shifted relative to a current pixel based on theexamining.

Various preferred features of the apparatus are set forth below.

The screen pixel identifier comprises a first mask of a predeterminedsize that is applied by centering the first mask on the pixel beingclassified to determine if the center pixel is in an area having apredetermined periodic pattern.

The first mask is divided into a plurality of overlapping areas, thecenter pixel being in each of the first mask areas.

The screen region verifier comprises a second mask of a predeterminedsize that is applied by centering the second mask on the pixel beingchecked.

The second mask is divided into a plurality of overlapping areas, thecenter pixel being in each of the second mask areas.

The predetermined periodic pattern is a periodic line or dot patternhaving a period of 2 or 3.

The low pass filter is selectively applied based on which of theplurality of second mask areas contains screen pixels.

The apparatus described above may further comprise a frequencyclassifier that determines a feature indicator for at least one portionof the image; and an image processor for adaptively sharpening orsoftening the at least one portion of the image based on the determinedfeature indicator.

In accordance with further aspects of the invention, the above-describedmethod or steps thereof may be embodied in a program of instructions(e.g., software) which may be stored on, or conveyed to, a computer orother processor-controlled device for execution. Alternatively, themethod or steps thereof may be implemented using hardware or acombination of software and hardware.

Other objects and attainments together with a fuller understanding ofthe invention will become apparent and appreciated by referring to thefollowing description and claims taken in conjunction with theaccompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

In the drawings wherein like reference symbols refer to like parts:

FIG. 1 is a block diagram illustrating major components in an imageprojection system that is suitable for carrying out various aspects ofthe present invention;

FIG. 2 is a block diagram illustrating components in a typical computersystem that is suitable for carrying out various aspects of theinvention;

FIG. 3 is a functional block diagram showing the process flow and therelationship between the keystone image artifact removal (KIAR) and theadaptive field-based video enhancement (AFBVE) operations;

FIG. 4 is a functional block diagram of the KIAR technique according toembodiments of the invention;

FIG. 5 is a schematic diagram of a screen pixel identifier (SPI) maskaccording to embodiments of the invention;

FIG. 6 is a schematic diagram of a screen region verifier (SRV) maskaccording to embodiments of the invention;

FIG. 7 is a schematic representation of a 3×3 Gaussian LPF kernel usedin embodiments of the invention;

FIG. 8 is a schematic representation showing the shift of the LPF kernelaccording to the SRV processing;

FIG. 9 is a functional block diagram of the AFBVE technique according toembodiments of the invention;

FIG. 10 is a graphical representation of the value of a featureindicator produced by a frequency classifier of the AFBVE operation as afunction of Sobel edge detector output;

FIG. 11A is a graphical representation of an interlaced input image; and

FIG. 11B is a schematic representation showing how a filter kernel, suchthe LPF kernel shown in FIG. 7, is applied to interlaced image data.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

FIG. 1 illustrates components in a typical image projection system 10 inwhich the techniques of the present invention can be employed. In theillustrated embodiment, a computer system 12, stores digital images thatare electrically transmitted along a suitable transmission path 14 to aprojecting device 16, such as a liquid crystal projector (LCP) whichprojects such images onto a screen, wall or other display area. As willbe appreciated by those skilled in the art, FIG. 1 represents just oneof many alternatives available for obtaining digital images andprojecting them. The present invention concerns certain processingapplied to the digital images before they are displayed or projected,and for the purpose of this invention, it is not important how or wherethe images are stored or digitized. Digital images to be processed inaccordance with the invention may be obtained from scanners, digitalcameras, etc., stored in a memory, and transmitted to the projectingdevice. Such digital images may also be computer generated. Moreover,the special processing which is the subject of the present invention mayoccur either in the projecting device itself, or in a computer or otherdevice capable of performing the processing of the invention prior totransmission of the processed image data to the projecting device.

In the case where digitized images are obtained, stored and processed bycomputer 12, such computer may be of any suitable type, including apersonal computer or workstation. As illustrated in FIG. 2, the computertypically includes a central processing unit (CPU) 21 that providescomputing resources and controls the computer. CPU 21 may be implementedwith a microprocessor or the like, and may also include a graphicsprocessor and/or a floating point coprocessor for mathematicalcomputations. Computer 12 further includes system memory 22 which may bein the form of random-access memory (RAM) and read-only memory (ROM).

A number of controllers and peripheral devices are also provided, asshown in FIG. 2. Input controllers 23 represents an interface to one ormore input devices 24, such as a keyboard, mouse or stylus. Computersystem 12 may also have input controllers for connecting an input devicesuch as a scanner and/or digital camera from which digital images may beobtained. A storage controller 25 is an interface to a storage device 26that includes a storage medium such as magnetic tape or disk, or anoptical medium that may be used to record programs of instructions foroperating systems, utilities and applications which may includeembodiments of programs that implement various aspects of the presentinvention. Storage device 26 may also be used to store image data to beprocessed in accordance with the invention. Output controllers 27provide interfaces to output devices 28 such as a display device whichmay be a cathode ray tube (CRT) or thin film transistor (TFT) display.An output controller is also provided for connecting projecting device16 to computer 12. Communications controller 29 interfaces withcommunication device 31 which may be a modem or other networkconnection. Programs that implement various aspects of this inventionand/or processed or to be processed image data may be transmitted tocomputer 12 from a remote location (e.g., a server) over a network.

In the illustrated embodiment, all major system components connect tobus 32 which may represent more than one physical bus. For example, somepersonal computers incorporate only a so-called Industry StandardArchitecture (ISA) bus. Other computers incorporate an ISA bus as wellas a higher bandwidth bus.

FIG. 3 illustrates a processor 100, which may be embodied in computer12, in the projecting device 16, or other suitable device, forperforming various functions, including keystone image artifact removal(KIAR) 35 and adaptive field-based video enhancement (AFBVE) 36 whichKIAR is designed to support. The relationship between KIAR and AFBVE isillustrated in the figure. The input image (I/P) is transmitted to theKIAR block where it is processed in accordance with the KIAR technique.The KIAR processed image is then transmitted to the AFBVE block where itmay be further processed in accordance with the AFBVE technique togenerate an output image (O/P) that is displayed by LCP 16.

The KIAR and AFBVE functions may be implemented in processor 100 in avariety of ways including by software, hardware, or combination thereof.Such software, for example, may be stored on computer 12 in systemmemory 22 or in storage device 26, and fetched by CPU 21 for execution.More broadly, such software may be conveyed by any of a variety ofmachine-readable medium including magnetic tape or disk, optical disc,signals transmitted through network paths including the Internet, aswell as other suitable carrier signals throughout the electromagneticspectrum including infrared signals. Processor 100 may also beimplemented with discrete logic circuits, one or more applicationspecific integrated circuits (ASICs), digital signal processors,program-controlled processors, or the like.

FIG. 4 is a functional block diagram of the KIAR technique in accordancewith embodiments of the invention. In one embodiment, KIAR 35 isimplemented with a screen pixel identifier (SPI) 41, a screen regionverifier (SRV) 42 and a filter 43 such as a low pass filter (LPF). Theprocess flow is as shown in the figure. SPI 41 examines each pixel of adigital image input to KIAR block 35 and classifies that pixel as eithera screen or non-screen pixel. For each pixel, SRV 42 then examinessurrounding area pixels to check if the initial classification wascorrect and to reclassify any pixels misclassified by SPI 41. A LPF isthen applied to screen region pixels, as described below, while keepingthe non-screen region pixels unchanged.

SPI 41 employs a mask 51, schematically illustrated in FIG. 5, toperform its classification function. In a preferred embodiment, mask 51has a size of 25×7 pixels and is centered on the pixel currently beingexamined, as illustrated in FIG. 5. The mask elements 52 are spaced soas to check if the center pixel is in a periodic line or dot patternarea, where the period or distance (dist) between pixels correspondingto adjacent mask elements is equal to some predetermined number. In apreferred embodiment, the mask elements 52 are spaced so thatpredetermined number is 3. That is, there are two pixels between eachpixel that corresponds to a mask element and that is examined. Inanother embodiment, mask 51 may also be sized such that dist=2, that is,every other pixel is examined.

As illustrated in FIG. 5, mask 51 is divided into overlapping quadrants,denoted (1), (2), (3) and (4). Such division is done to facilitate theidentification of screen pixels on borders and in corners. In apreferred embodiment, each quadrant covers 13×4 pixels, i.e., a 5×2cycle of pixels. The right-most column of pixels in quadrant (1) overlapwith the left-most column of pixels in quadrant (2), and the bottom rowof pixels in quadrant (1) overlap with the top row of pixels in quadrant(3). Similarly, the top row of pixels in quadrant (4) overlap with thebottom row of pixels of quadrant (2), and the left-most column of pixelsin quadrant (4) overlap with the right-most column of pixels in quadrant(3). The center pixel is common to each quadrant.

In one embodiment, if all examined pixels in a particular quadrant havethe same color values (e.g., RGB values), then that quadrant isconsidered to be in a screen area with a predetermined screen patternperiod corresponding to the SPI mask used. Other pixel attributes, suchas luminosity or chrominance, may also be examined for patternscorresponding to the predetermined pattern. If any quadrant isclassified as being in a screen area, then the center pixel isconsidered a screen pixel.

After processing with the SPI mask, whereby all pixels are designated asa screen or a non-screen pixel, any pixel misclassifications arecorrected by SRV 42 which also employs a mask, similar to the SPI maskbut of different dimensions. Thus, for each pixel, SRV 42 is used tocheck whether each quadrant contains only screen pixels, that is, if allpixels in a particular quadrant were determined by the SPI mask to bescreen pixels. When the SPI mask is 25×7, as shown in FIG. 5, the SRVmask 61 is preferably 25×5 pixels and also divided into quadrantsdenoted [1], [2], [3] and [4], as illustrated in FIG. 6. Each quadrantis preferably 13×3 pixels with one horizontal and vertical line overlapbetween adjacent quadrants, as is the case with the SPI mask. Dividingthe SRV mask 61 into quadrants allows the SRV to perform accurately bothinside screen regions and at the borders and corners of such regions.

A filter kernel of LPF 43 is applied based on the processing with theSRV mask. The filter kernel is preferably a 3×3 Gaussian LPF kernelwhose coefficients are shown in FIG. 7. The manner in which the LPFkernel is applied depends on which combination of quadrants of the SRVmask 61 contain screen pixels. If all of the pixels in each of the fourquadrants of SRV mask 61 are screen pixels, then the LPF kernel isapplied to smooth the center pixel, which is the darkened pixel in FIG.6. However, in other combinations, the LPF kernel is shifted before itis applied, as illustrated in FIG. 8. If only quadrants [1] and [2]contain screen pixels, the LPF kernel is moved one pixel up. If onlyquadrants [3] and [4] contain screen pixels, the LPF kernel is moved onepixel down. If only quadrants [1] and [3] contain screen pixels, the LPFkernel is moved one pixel to the left. If only quadrants [2] and [4]contain screen pixels, the LPF kernel is moved one pixel to the right.If only quadrant [1] contains screen pixels, the LPF kernel is moved onepixel diagonally to the upper left. If only quadrant [2] contains screenpixels, the LPF kernel is moved one pixel diagonally to the upper right.If only quadrant [3] contains screen pixels, the LPF kernel is moved onepixel diagonally to the lower left. If only quadrant [4] contains screenpixels, the LPF kernel is moved one pixel diagonally to the lower right.In all other cases, the pixel being examined is left unchanged. That is,the LPF is not applied.

For a pixel (i, j), the LPF process is as follows:

I_(i/p) (i, j)=input image of KIAR operation

I_(lpf) (i, j)=3×3 Gaussian LPF with center shifted as shown in FIG. 8

I_(hpf) (i, j)=I_(i/p) (i, j)−I_(lpf) (i, j)

I_(o/p) (i, j)=output image of KIAR operation=I_(lpf) (i,j)+(1+sharpening factor) *I_(hpf) (i, j)

While the sharpening factor may be experimentally determined for a givenLCP system based on the system's hardware characteristics, the inventorshave experimentally determined that a value for the term (1+sharpeningfactor)=1/8. Such a value reduced moiré artifacts in screen areas underall keystone operations on a test image. For non-screen areas, theoutput image is made to be the same as the input image to maintainnon-screen areas of the image.

As previously noted, the KIAR technique may be employed with anothertechnique known as Adaptive Field-Based Video Enhancement (AFBVE). Inthis case, the KIAR processed image is passed to the AFBVE block forfurther smoothing or sharpening, as determined by the AFBVE technique.AFBVE is an adaptive process that is used to smooth or sharpen edges orboundaries, as needed, to remove blurring caused by interlaced videoinput, which is the separate input to the LCP of odd and even imagepixel lines. With interlaced video input, usually the odd pixel linesare input first, followed by the even pixel lines. Either way, such aninput results in each video frame being comprised of two fields: an oddline field and an even line field. These interaction between these twofields tends to cause blurring in the resulting image. AFBVE is designedto correct this type of blurring.

FIG. 9 is a functional block diagram of the AFBVE technique whichadaptively applies sharpening and smoothing to the digital output of theKIAR block 35. The output of KIAR 35 forms the input image, which isinterlaced or progressive data, to AFBVE 36. This input image istransmitted to LPF 91, a first summing function 92, and a frequencyclassifier 93.

LPF 91 low-pass filters the input image to obtain a smooth (i.e.,softened image). LPF 91 preferably uses the same 3×3 Gaussian kernelillustrated in FIG. 7. The smoothened image is subtracted from the inputimage to obtain the high pass frequency components of the image whichforms the other input to first summing function 92. Element 92 combinesthe input image and the high pass frequency components and transmits theresult to a scale factor determiner 94 which generates a scaling factorfor magnifying the high frequency components of the image. A scalingfactor of 1 means that the output image of the AFBVE function is to bethe same as the function's input image; a scaling factor greater than 1means the output image is to be sharpened; and a scaling factor of lessthan 1 means the output image is to be softened. The inventors haveexperimentally determined a preferred scaling factor of 1+20/32=52/32.

Rather than simply magnifying the high frequency components by thescaling factor, and then adding them on to the smoothed image to producethe output (O/P) image, the frequency classifier 93 of the presentinvention produces a feature indicator, denoted by “ƒ” in FIG. 9, tomodulate the scaling factor to achieve adaptive sharpening and softeningenhancement. Frequency classifier 93 determines which image areas are tobe sharpened and which are to be softened and also determines themagnitude of the sharpening or softening factor to be applied at eachpixel location in the image. That is, frequency classifier 93 detectsimage spatial frequency information in order to separate primary edgesfrom noisy micro-edges (or non-edges) to produce the feature indicator,ƒ.

Specifically, frequency classifier 93 uses 3×3 Sobel edge detectors todetect spatial frequency components of the image and classify eachcomponent into one of the three regions illustrated in FIG. 10. Thethree regions are: a softening region which is below a predeterminedlower threshold frequency (thr_low), a sharpening region above apredetermined upper threshold (thr_high), and a transition regionbetween the softening and sharpening regions. The transition regionprovides a smooth transition between softening and sharpeningenhancement. As shown in FIG. 10, ƒ is linear in the transition regionto avoid discontinuity artifacts between the softening and sharpeningregions.

As shown in FIG. 10, feature indicator, ƒ, is a function of the outputof the Sobel edge detectors, which has a range of 0-255. The thr_low andthr_high will vary depending on the type of image, personal visualpreferences and system hardware characteristics. Such thresholds can beexperimentally determined. However, the inventors have determined thatfor many images a thr_low of about 20 and thr_high of about 40 yieldsgood results.

The feature indicator ƒ, which is number from 0 to 1 (expressed as apercentage between 0 and 100% in FIG. 10), is input to a multiplier 95where it is multiplied with the scaling factor of scale factordeterminer 94 to produce a modulated scaling factor which is applied bya summer 96 to the smoothed image produced by LPF 91. A modulatedscaling factor of 1 means that no change is applied to output of LPF 91;a scaling factor greater than 1 means that such output is sharpened; anda scaling factor of less than 1 means that such output is softened orsmoothed. The resulting image from summer 96 is the output (O/P) imageof the AFBVE process.

FIG. 11A is a graphical representation of an interlaced video imagewhich may be input to an LCP. As previously discussed, in an interlacedimage format, each frame contains two fields: a first field whichcontains, say, all of the odd scan lines and a second field whichcontains, say, all of the even scan lines. Each image data field isprocessed separately, for example, the first field is processed followedby the second field. Thus, in the filtering process, a filter kernel isapplied to elements from either the first or the second fields, asschematically illustrated in FIG. 11B. It should be noted that theinterlaced video format is only one type of video input for an LCP. Aprogressive format, an image of which has a line-by-line raster format,may also be used.

As the foregoing description demonstrates, the present inventionprovides a technique (KIAR) for smoothing non-screen image regions toremove moiré therefrom while maintaining sharpness in the non-screenregions. The KIAR process may be followed by an AFBVE process, each ofwhich may be conveniently implemented in a personal computer or otherprocessing device using software, hardware, or combination thereof.

With these implementation alternatives in mind, it is to be understoodthat the block and flow diagrams show the performance of certainspecified functions and relationships thereof. The boundaries of thesefunctional blocks have been arbitrarily defined herein for convenienceof description. Alternate boundaries may be defined so long as thespecified functions are performed and relationships therebetween areappropriately maintained. The diagrams and accompanying descriptionprovide the functional information one skilled in the art would requireto fabricate circuits or to write software code to perform theprocessing required.

While the invention has been described in conjunction with severalspecific embodiments, many further alternatives, modifications,variations and applications will be apparent to those skilled in the artthat in light of the foregoing description. Thus, the inventiondescribed herein is intended to embrace all such alternatives,modifications, variations and applications as may fall within the spiritand scope of the appended claims.

1. A method for removing image artifacts from a representation of animage, comprising the steps of: (a) obtaining a pixel representation ofthe image; (b) classifying each pixel in the image as a screen ornon-screen pixel, wherein a screen pixel is defined as a pixel that ispart of a predetermined periodic pattern; (c) examining pixels in apredetermined surrounding area of each pixel to check the classificationof that pixel as determined in step (b) by applying a two-dimensionalmask that is divided into a plurality of quadrants, the center of thetwo-dimensional mask being common to each of the quadrants; and (d)selectively applying a low pass filter to pixels in the image, suchthat, when the low pass filter is applied, a center of the low passfilter is selectively shifted relative to a current pixel based on whichof the plurality of quadrants in the two-dimensional mask containsscreen pixels as determined in the examining in step (c).
 2. The methodof claim 1, wherein the classifying step (b) comprises applying a maskthat is divided into overlapping areas with the center of the mask beingcommon to each of the areas, the mask being applied such that it iscentered on the pixel being classified to determine if the center pixelis part of the predetermined periodic pattern.
 3. The method of claim 2,wherein the predetermined periodic pattern is a periodic line or dotpattern having, a period of 2 or
 3. 4. The method of claim 1, wherein,in the examining step (c), the two-dimensional mask is applied such thatit is centered on the pixel being checked.
 5. The method of claim 1,further comprising the steps of: (e) determining a feature indicator forat least one portion of the image; and (f) adaptively sharpening orsoftening the at least one portion of the image based on the determinedfeature indicator.
 6. An apparatus for removing image artifacts from arepresentation of an image, the apparatus comprising: a device forobtaining a pixel representation of the image; a screen pixelidentifier, in communication with the device, for classifying each pixelin the image as a screen or non-screen pixel, wherein a screen pixel isdefined as a pixel that is part of a predetermined periodic pattern; ascreen region verifier, in communication with the screen pixelidentifier, that includes a two-dimensional mask divided into aplurality of quadrants, the center of the two-dimensional mask beingcommon to each of the quadrants, for examining pixels in a predeterminedsurrounding area of each pixel to check the classification of that pixelas determined by the screen pixel identifier; and a low pass filter, incommunication with the screen region verifier, that is selectivelyapplied to pixels in the image, such that, when the low pass filter isapplied, a center of the low pass filter is selectively shifted relativeto a current pixel based on which of the plurality of quadrants in thetwo-dimensional mask contains screen pixels as determined in theexamining operation.
 7. The apparatus of claim 6, wherein the screenpixel identifier comprises a mask that is divided into overlapping areaswith the center of the mask being common to each of the areas and thatis applied by centering the mask on the pixel being classified todetermine if the center pixel is part of the predetermined periodicpattern.
 8. The apparatus of claim 7, wherein the predetermined periodicpattern is a periodic line or dot pattern having a period of 2 or
 3. 9.The apparatus of claim 6, wherein the two-dimensional mask is applied bycentering it on the pixel being checked.
 10. The apparatus of claim 6,further comprising: a frequency classifier that determines a featureindicator for at least one portion of the image; and an image processorfor adaptively sharpening or softening the at least one portion of theimage based on the determined feature indicator.
 11. A machine-readablemedium embodying a program of instructions for causing a machine toperform a method of removing image artifacts from a representation of animage, the program of instructions comprising instructions for: (a)obtaining a pixel representation of the image; (b) classifying eachpixel in the image as a screen or non-screen pixel, wherein a screenpixel is defined as a pixel that is part of a predetermined periodicpattern; (c) examining pixels in a predetermined surrounding area ofeach pixel to check the classification of that pixel as determined bythe classifying instruction (b) by applying a two-dimensional mask thatis divided into a plurality of quadrants, the center of thetwo-dimensional mask being common to each of the quadrants; and (d)selectively applying a low pass filter to pixels in the image, suchthat, when the low pass filter is applied, a center of the low passfilter is selectively shifted relative to a current pixel based on whichof the plurality of quadrants in the two-dimensional mask containsscreen pixels as determined by the result of the examining instruction(c).
 12. The machine-readable medium of claim 11, wherein theclassifying instruction (b) comprises applying a mask that is dividedinto overlapping areas with the center of the mask being common to eachof the areas, the mask being applied such that it is centered on thepixel being classified to determine if the center pixel is part of thepredetermined periodic pattern.
 13. The machine-readable medium of claim12, wherein the predetermined periodic pattern is a periodic line or dotpattern having a period of 2 or
 3. 14. The machine-readable medium ofclaim 11, wherein, in the execution of the examining instruction (c),the two-dimensional mask is applied such that it is centered on thepixel being checked.
 15. The machine-readable medium of claim 11,further comprising instructions for: (e) determining a feature indicatorfor at least one portion of the image; and (f) adaptively sharpening orsoftening the at least one portion of the image based on the determinedfeature indicator.